Diane Oyen - RankMe

54 papers A* 3A 2C 1Misc 2Journal 30Unranked 16

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Out-of-distribution transfer of PDE foundation models to material dynamics under extreme loading. CoRR Mahindra Singh Rautela, Alexander Most, Siddharth Mansingh, Aleksandra Pachalieva, Bradley C. Love, Daniel O'Malley, Alexander Scheinker, Kyle Hickmann, Diane Oyen, Nathan DeBardeleben, Earl Lawrence, Ayan Biswas
2026	J	`jnl`	PDE foundation model-accelerated inverse estimation of system parameters in inertial confinement fusion. CoRR Mahindra Singh Rautela, Alexander Scheinker, Bradley C. Love, Diane Oyen, Nathan DeBardeleben, Earl Lawrence, Ayan Biswas
2025	J	`jnl`	MORPH: Shape-agnostic PDE Foundation Models. CoRR Mahindra Singh Rautela, Alexander Most, Siddharth Mansingh, Bradley C. Love, Ayan Biswas, Diane Oyen, Earl Lawrence
2025	J	`jnl`	SPUS: A Lightweight and Parameter-Efficient Foundation Model for PDEs. CoRR Abu Bucker Siddik, Diane Oyen, Alexander Most, Michal Kucer, Ayan Biswas
2025	J	`jnl`	Towards Reasoning for PDE Foundation Models: A Reward-Model-Driven Inference-Time-Scaling Algorithm. CoRR Siddharth Mansingh, James Amarel, Ragib Arnab, Arvind T. Mohan, Kamaljeet Singh, Gerd J. Kunde, Nicolas Hengartner, Benjamin Migliori, Emily Casleton, Nathan DeBardeleben, Ayan Biswas, Diane Oyen, Earl Lawrence
2024	Misc	`conf`	Graph Neural Networks for Parameterized Quantum Circuits Expressibility Estimation. QCE Shamminuj Aktar, Andreas Bärtschi, Diane Oyen, Stephan J. Eidenbenz, Abdel-Hameed A. Badawy
2024	J	`jnl`	Graph Neural Networks for Parameterized Quantum Circuits Expressibility Estimation. CoRR Shamminuj Aktar, Andreas Bärtschi, Diane Oyen, Stephan J. Eidenbenz, Abdel-Hameed A. Badawy
2023	J	`jnl`	DeepPatent2: A Large-Scale Benchmarking Corpus for Technical Drawing Understanding. CoRR Kehinde Ajayi, Xin Wei, Martin Gryder, Winston Shields, Jian Wu, Shawn M. Jones, Michal Kucer, Diane Oyen
2023	J	`jnl`	Discovering Image Usage Online: A Case Study With "Flatten the Curve". CoRR Shawn M. Jones, Diane Oyen
2023	—	`conf`	Discovering Image Usage Online: A Case Study with "Flatten the Curve". JCDL Shawn M. Jones, Diane Oyen
2023	Misc	`conf`	Predicting Expressibility of Parameterized Quantum Circuits Using Graph Neural Network. QCE Shamminuj Aktar, Andreas Bärtschi, Abdel-Hameed A. Badawy, Diane Oyen, Stephan J. Eidenbenz
2023	J	`jnl`	Semi-supervised Learning of Pushforwards For Domain Translation & Adaptation. CoRR Nishant Panda, Natalie Klein, Dominic Yang, Patrick Gasda, Diane Oyen
2022	—	`conf`	Abstract Images Have Different Levels of Retrievability Per Reverse Image Search Engine. ECCV Workshops (8) Shawn M. Jones, Diane Oyen
2022	J	`jnl`	Abstract Images Have Different Levels of Retrievability Per Reverse Image Search Engine. CoRR Shawn M. Jones, Diane Oyen
2022	A	`conf`	DeepPatent: Large scale patent drawing recognition and retrieval. WACV Michal Kucer, Diane Oyen, Juan Castorena, Jian Wu
2022	J	`jnl`	Generative structured normalizing flow Gaussian processes applied to spectroscopic data. CoRR Natalie Klein, Nishant Panda, Patrick Gasda, Diane Oyen
2022	J	`jnl`	Quantum Algorithm Implementations for Beginners. ACM Trans. Quantum Comput. Abhijith Jayakumar, Adetokunbo Adedoyin, John Ambrosiano, Petr M. Anisimov, William Casper, Gopinath Chennupati, Carleton Coffrin, Hristo N. Djidjev, David Gunter, Satish Karra, Nathan Lemons, Shizeng Lin, Alexander Malyzhenkov, David Mascarenas, Susan M. Mniszewski, Balu Nadiga, Daniel O'Malley, Diane Oyen, Scott Pakin, Lakshman Prasad, Randy Roberts, Phillip Romero, Nandakishore Santhi, Nikolai Sinitsyn, Pieter J. Swart, James G. Wendelberger, Boram Yoon, Richard J. Zamora, Wei Zhu, Stephan J. Eidenbenz, Andreas Bärtschi, Patrick J. Coles, Marc Vuffray, Andrey Y. Lokhov
2022	J	`jnl`	Robustness to Label Noise Depends on the Shape of the Noise Distribution in Feature Space. CoRR Diane Oyen, Michal Kucer, Nick Hengartner, Har Simrat Singh
2022	A*	`conf`	Robustness to Label Noise Depends on the Shape of the Noise Distribution. NeurIPS Diane Oyen, Michal Kucer, Nicolas W. Hengartner, Har Simrat Singh
2022	—	`conf`	Segmenting Technical Drawing Figures in US Patents. SDU@AAAI Md Reshad Ul Hoque, Xin Wei, Muntabir Hasan Choudhury, Kehinde Ajayi, Martin Gryder, Jian Wu, Diane Oyen
2022	—	`conf`	Spectroscopynet: Learning to Pre-Process Spectroscopy Signals Without Clean Data. IEEECONF Juan Castorena, Diane Oyen
2022	—	`conf`	Visual descriptor extraction from patent figure captions: a case study of data efficiency between BiLSTM and transformer. JCDL Xin Wei, Jian Wu, Kehinde Ajayi, Diane Oyen
2021	J	`jnl`	Diff2Dist: Learning Spectrally Distinct Edge Functions, with Applications to Cell Morphology Analysis. CoRR Cory Braker Scott, Eric Mjolsness, Diane Oyen, Chie Kodera, David Bouchez, Magalie Uyttewaal
2021	—	`conf`	Fast Gaussian Process Estimation for Large-Scale In Situ Inference using Convolutional Neural Networks. IEEE BigData Divya Banesh, Nishant Panda, Ayan Biswas, Luke Van Roekel, Diane Oyen, Nathan M. Urban, Michael Grosskopf, Jonathan David Wolfe, Earl Lawrence
2021	J	`jnl`	Learning to Pre-process Laser Induced Breakdown Spectroscopy Signals Without Clean Data. CoRR Juan Castorena, Diane Oyen
2021	J	`jnl`	Neural density estimation and uncertainty quantification for laser induced breakdown spectroscopy spectra. CoRR Katiana Kontolati, Natalie Klein, Nishant Panda, Diane Oyen
2021	J	`jnl`	On visual self-supervision and its effect on model robustness. CoRR Michal Kucer, Diane Oyen, Garrett T. Kenyon
2021	—	`conf`	Recognizing Figure Labels in Patents. SDU@AAAI Ming Gong, Xin Wei, Diane Oyen, Jian Wu, Martin Gryder, Liping Yang
2020	J	`jnl`	Deep Spectral CNN for Laser Induced Breakdown Spectroscopy. CoRR Juan Castorena, Diane Oyen, Ann Ollila, Carey Legget, Nina Lanza
2020	—	`conf`	Diagram Image Retrieval using Sketch-Based Deep Learning and Transfer Learning. CVPR Workshops Manish Bhattarai, Diane Oyen, Juan Castorena, Liping Yang, Brendt Wohlberg
2020	J	`jnl`	Diagram Image Retrieval using Sketch-Based Deep Learning and Transfer Learning. CoRR Manish Bhattarai, Diane Oyen, Juan Castorena, Liping Yang, Brendt Wohlberg
2020	—	`conf`	Learning Shapes on Image Sampled Points with Dynamic Graph CNNs. SSIAI Juan Castorena, Diane Oyen
2020	—	`conf`	Learning Spatial Relationships between Samples of Patent Image Shapes. CVPR Workshops Juan Castorena, Manish Bhattarai, Diane Oyen
2020	J	`jnl`	Learning Spatial Relationships between Samples of Patent Image Shapes. CoRR Juan Castorena, Manish Bhattarai, Diane Oyen
2020	J	`jnl`	Mesoscale informed parameter estimation through machine learning: A case-study in fracture modeling. J. Comput. Phys. Nishant Panda, Dave Osthus, Gowri Srinivasan, Daniel O'Malley, Viet T. Chau, Diane Oyen, Humberto Godinez
2020	—	`conf`	Physics-Informed Spatiotemporal Deep Learning for Emulating Coupled Dynamical Systems. AAAI Spring Symposium: MLPS Anishi Mehta, Cory Braker Scott, Diane Oyen, Nishant Panda, Gowri Srinivasan
2020	J	`jnl`	StressNet: Deep Learning to Predict Stress With Fracture Propagation in Brittle Materials. CoRR Yinan Wang, Diane Oyen, Weihong Guo, Anishi Mehta, Cory Braker Scott, Nishant Panda, M. Giselle Fernández-Godino, Gowri Srinivasan, Xiaowei Yue
2020	J	`jnl`	TGGLines: A Robust Topological Graph Guided Line Segment Detector for Low Quality Binary Images. CoRR Ming Gong, Liping Yang, Catherine Potts, Vijayan K. Asari, Diane Oyen, Brendt Wohlberg
2019	—	`conf`	A Novel Algorithm for Skeleton Extraction From Images Using Topological Graph Analysis. CVPR Workshops Liping Yang, Diane Oyen, Brendt Wohlberg
2019	—	`conf`	A Topological Graph-Based Representation for Denoising Low Quality Binary Images. ICCV Workshops Catherine Potts, Liping Yang, Diane Oyen, Brendt Wohlberg
2019	A	`conf`	Learning Diverse Gaussian Graphical Models and Interpreting Edges. SDM Roozbeh Yousefzadeh, Diane Oyen, Nina Lanza
2019	J	`jnl`	The ISTI Rapid Response on Exploring Cloud Computing 2018. CoRR Carleton Coffrin, James Arnold, Stephan J. Eidenbenz, Derek Aberle, John Ambrosiano, Zachary K. Baker, Sara Brambilla, Michael J. Brown, K. Nolan Carter, Pinghan Chu, Patrick Conry, Keeley Costigan, Ariane Eberhardt, David M. Fobes, Adam Gausmann, Sean N. Harris, Donovan Heimer, Marlin Holmes, Bill Junor, Csaba Kiss, Steve Linger, Rodman R. Linn, Li-Ta Lo, Jonathan MacCarthy, Omar Marcillo, Clay McGinnis, Alexander McQuarters, Eric Michalak, Arvind T. Mohan, Matt Nelson, Diane Oyen, Nidhi Parikh, Donatella Pasqualini, Aaron S. Pope, Reid B. Porter, Chris Rawlings, Hannah Reinbolt, Reid D. Rivenburgh, Philip Romero, Kevin Schoonover, Alexei N. Skurikhin, Daniel R. Tauritz, Dima Tretiak, Zhehui Wang, James Wernicke, Brad Wolfe, Phillip Wolfram, Jonathan Woodring
2018	J	`jnl`	Quantum Algorithm Implementations for Beginners. CoRR Patrick J. Coles, Stephan J. Eidenbenz, Scott Pakin, Adetokunbo Adedoyin, John Ambrosiano, Petr M. Anisimov, William Casper, Gopinath Chennupati, Carleton Coffrin, Hristo N. Djidjev, David Gunter, Satish Karra, Nathan Lemons, Shizeng Lin, Andrey Y. Lokhov, Alexander Malyzhenkov, David Mascarenas, Susan M. Mniszewski, Balu Nadiga, Dan O'Malley, Diane Oyen, Lakshman Prasad, Randy Roberts, Philip Romero, Nandakishore Santhi, Nikolai Sinitsyn, Pieter J. Swart, Marc Vuffray, Jim Wendelberger, Boram Yoon, Richard J. Zamora, Wei Zhu
2017	J	`jnl`	Order priors for Bayesian network discovery with an application to malware phylogeny. Stat. Anal. Data Min. Diane Oyen, Blake Anderson, Kari Sentz, Christine M. Anderson-Cook
2016	—	`conf`	Bayesian Networks with Prior Knowledge for Malware Phylogenetics. AAAI Workshop: Artificial Intelligence for Cyber Security Diane Oyen, Blake Anderson, Christine M. Anderson-Cook
2016	J	`jnl`	Learning Planar Ising Models. J. Mach. Learn. Res. Jason K. Johnson, Diane Oyen, Michael Chertkov, Praneeth Netrapalli
2015	—	`conf`	Discovering compositional trends in Mars rock targets from ChemCam spectroscopy and remote imaging. AIPR Diane Oyen, Nina Lanza, Reid B. Porter
2015	C	`conf`	Learning Watershed Cuts Energy Functions. ISMM Reid B. Porter, Diane Oyen, Beate G. Zimmer
2015	J	`jnl`	Transfer learning for Bayesian discovery of multiple Bayesian networks. Knowl. Inf. Syst. Diane Oyen, Terran Lane
2013	A*	`conf`	Bayesian Discovery of Multiple Bayesian Networks via Transfer Learning. ICDM Diane Oyen, Terran Lane
2013	J	`jnl`	Bayesian Discovery of Multiple Bayesian Networks via Transfer Learning. CoRR Diane Oyen, Terran Lane
2013	J	`jnl`	Controlling the Precision-Recall Tradeoff in Differential Dependency Network Analysis. CoRR Diane Oyen, Alexandru Niculescu-Mizil, Rachel Ostroff, Alex Stewart, Vincent P. Clark
2012	A*	`conf`	Leveraging Domain Knowledge in Multitask Bayesian Network Structure Learning. AAAI Diane Oyen, Terran Lane
2011	—	`conf`	Active Learning of Transfer Relationships for Multiple Related Bayesian Network Structures. ICDM Workshops Diane Oyen